In the previous two methods, the downstream generation model learns how to filter out irrelevant or even harmful information from the retrieved examples implicitly. There also exist some works that try to explicitly extract useful information, i.e., skeleton extraction, from the retrieved memory [1]}, [2]}, [3]}. For example, one skeleton should be a part of a whole utterance with irrelevant content masked, and the generation model only integrate this skeleton in the generation process.
